causal graph modeling 1cognitive map learning 1differentiable programming 1spatial representation 1vector quantized autoencoder 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Differentiable Clone-Structured Causal Graphs for End-to-End Cognitive Map Learning from Image Sequences
Arash Nikzad, Sasan Sarbishegi, Ali Dasmeh +8
The paper presents gradCSCG, a fully differentiable version of the Clone-Structured Causal Graph model, integrated with a vector-quantized VAE to enable end‑to‑end learning of cogn…
cs.CY2026
The Price of Prompting: Profiling Energy Use in Large Language Models Inference
Erik Johannes Husom, Arda Goknil, Lwin Khin Shar +1
In the rapidly evolving realm of artificial intelligence, deploying large language models (LLMs) poses increasingly pressing computational and environmental challenges. This paper…
cs.CY2025
Sustainable LLM Inference for Edge AI: Evaluating Quantized LLMs for Energy Efficiency, Output Accuracy, and Inference Latency
Erik Johannes Husom, Arda Goknil, Merve Astekin +5
Deploying Large Language Models (LLMs) on edge devices presents significant challenges due to computational constraints, memory limitations, inference speed, and energy consumption…